Savage, MT
How exposed is Savage to wildfire?
USFS scores Savage at the 63rd national percentile for wildfire risk to structures (well above the national norm for wildfire risk), a figure built from 237 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Savage at the 60th national percentile — 3 points below its risk-to-structures score, a gap driven by how much is actually built there.
What "at risk" means for the buildings here
Indirect exposure is dominant in Savage (87.3% of 237 buildings): far enough from burnable vegetation to avoid flame contact, close enough for wind-blown embers. Only 12.2% sit in the Direct zone.
Where Savage ranks
Inside Montana, Savage sits at just the 29th percentile even though it scores 63rd nationally — the state's overall wildfire exposure is high enough to make this a relatively quiet corner of it. Among the 31,521 US communities USFS scores, Savage ranks 11,792 for wildfire risk (1 is highest) and 23,561 by building count (1 is largest). Within Montana alone, it ranks 339 of 475 places by risk. See the full county-by-county picture for Montana on its state page.
What this risk score means for insurance
Savage's 63rd-percentile, high rating is the kind of score behind a broader national pattern: insurers pulling back from the highest wildfire-risk markets, non-renewing or declining new policies outright, most visibly in California. Shopping around, not assuming automatic renewal, tends to matter here.
Hardening a home in Savage
Because 87.3% of Savage's buildings sit in the Indirect zone, sealing the ember pathway (vents, roofing, gutters) is the intervention this page's data actually supports — see the home-hardening guide.
Where Savage's figures come from
Savage's 63rd-percentile score and its burn-probability figure both come from the same USFS workbook, documented in the methodology guide. The exposure-zones guide covers what Savage's dominant indirect exposure actually means, with real examples from across the dataset.